Steerable CNNs

Learning Steerable Filters for Rotation Equivariant CNNs

In many machine learning tasks it is desirable that a model’s prediction transforms in an equivariant way under transformations of its input. Convolutional neural networks (CNNs) implement translational equivariance by construction; for other transformations, however, they are compelled to learn the proper mapping. In this work, we develop Steerable Filter CNNs (SFCNNs) which achieve joint equi...

Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks)

Group equivariant and steerable convolutional neural networks (regular and steerable G-CNNs) have recently emerged as a very effective model class for learning from signal data such as 2D and 3D images, video, and other data where symmetries are present. In geometrical terms, regular G-CNNs represent data in terms of scalar fields (“feature channels”), whereas the steerable G-CNN can also use v...

افزایش کنترل دقیقTVD در حفاری افقی به وسیله Rotary Steerable System RSS در میدان نفتی فروزان

Convolutional Gating Network for Object Tracking

Object tracking through multiple cameras is a popular research topic in security and surveillance systems especially when human objects are the target. However, occlusion is one of the challenging problems for the tracking process. This paper proposes a multiple-camera-based cooperative tracking method to overcome the occlusion problem.  The paper presents a new model for combining convolutiona...

Drilling Trajectory Prediction Model for Push-the-bit Rotary Steerable Bottom Hole Assembly

The study of rotary steering drilling technology is currently one of the hot topics in the drilling engineering field. It requires accurate well trajectory control instructions when rotary steerable tools are applied to achieve the well trajectory control goal. A drilling trajectory prediction model will benefit this progress. According to the continuous beam theory, a mechanical model of push-...